multicomp.order
Update a multicomp object by ordering its contrasts.
Update a multicomp object by ordering its contrasts.
The default sort.by = "height"
matches the order in the MMC plot.
An alternate sort.by = "estimate"
matches the order of the
half-normal plot. Or the argument sort.order
can be used
to specify any other order.
- Keywords
- dplot
Usage
multicomp.order(mca, sort.by = "height", sort.order = NULL)multicomp.label.change(x, old="adj", new="new", how.many=2)
## S3 method for class 'multicomp':
multicomp.label.change(x, old="adj", new="new", how.many=2)
## S3 method for class 'mmc.multicomp':
multicomp.label.change(x, old="adj", new="new", how.many=2)
Arguments
- mca
"multicomp"
object. This is the result ofmulticomp
in S-Plus or the result from applyingas.multicomp
to a"glht"
object in R.- sort.by
- Either
"height"
or"estimate"
. - sort.order
- Vector of indices by which the contrasts are to be
sorted. When
sort.order
in non-NULL
, it is used. - x
"multicomp"
object.- old
- character string to be removed from contrast names.
- new
- replacement character string to be inserted in contrast names.
- how.many
- number of times to make the replacement.
Value
- The result is a
"multicomp"
object containing the same contrasts as the argument.multicomp.order
sorts the contrasts (and renames them consistently) according to the specifications.multicomp.label.change
changes the contrast names according to the specifications.When
sort.by=="height"
, sort the contrasts by the reverse order of the heights. This provides a"multicomp"
object that will be plotted byplot.multicomp
in the same order used bymmcplot
or the olderplot.mmc.multicomp
. If there is not"height"
component, the original"multicomp"
object is returned.When
sort.by=="estimate"
, sort the contrasts by the reverse order of the contrast estimates. This provides the same order as the half-normal plot.When
sort.order
in non-NULL
, sort the contrasts in that order.
Note
S-Plus use the multicomp
functions
and R uses the multcomp
package.
References
Heiberger, Richard M. and Holland, Burt (2004b). Statistical Analysis and Data Display: An Intermediate Course with Examples in S-Plus, R, and SAS. Springer Texts in Statistics. Springer. ISBN 0-387-40270-5.
Heiberger, Richard M. and Holland, Burt (2006). "Mean--mean multiple comparison displays for families of linear contrasts." Journal of Computational and Graphical Statistics, 15:937--955.
See Also
MMC
, as.glht in R
,
multicomp.reverse
Examples
## continue with the example in mmc in R, or multicomp.mmc in S-Plus
data(catalystm)
catalystm1.aov <- aov(concent ~ catalyst, data=catalystm)
if.R(r={
catalystm.mca <-
glht(catalystm1.aov, linfct = mcp(catalyst = "Tukey"))
print(confint(catalystm.mca))
catalystm.mmc <-
mmc(catalystm1.aov, linfct = mcp(catalyst = "Tukey"))
## the contrasts have been ordered by height (see ?MMC),
## which in this example corresponds to sort.order=c(1,2,4,3,5,6),
## and reversed, to make the contrast Estimates positive.
print(as.glht(catalystm.mmc$mca))
## ## For consistency with the S-Plus example,
## ## we change all factor level "A" to "control".
## as.glht(multicomp.label.change(catalystm.mmc$mca, "A", "control"))
},s={
catalystm.mca <-
multicomp(catalystm1.aov, method="Tukey")
print(catalystm.mca)
catalystm.mmc <-
multicomp.mmc(catalystm1.aov, method="Tukey", plot=FALSE)
## the contrasts have been ordered by height (see ?MMC),
## which in this example corresponds to sort.order=c(1,2,4,3,5,6),
## and reversed, to make the contrast Estimates positive.
print(catalystm.mmc$mca)
## S-Plus multicomp already uses simple names. This function is
## therefore used in more complex two-way ANOVA examples. We illustrate
## here by changing all factor level "A" to "control".
print(multicomp.label.change(catalystm.mmc$mca, "A", "control"))
})